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Lulc Classification by Semantic Segmentation of Satellite Images Using Fastfcn by Bayu Rizqi is a document available to read on EtoBox.

This paper explores the effectiveness of the Fast Fully Convolutional Network (FastFCN) for semantic segmentation of satellite images to classify Land Use/Land Cover (LULC) into five categories: BuiltUp, Meadow, Farmland, Water, and Forest. The study demonstrates that FastFCN achieves superior performance metrics, including an accuracy of 0.93 and a mean Intersection over Union (mIoU) of 0.97, compared to existing methods like FCN-8 and eCognition. The results suggest that FastFCN is a promising automated a

Author

Bayu Rizqi

Language

EN